The topic I investigated is the difference between music by musicians with perfect pitch (PP) vs relative pitch (RP). In a lot of musical scenes, perfect pitch (or absolute pitch) is adored like it is some kind of godsend. On one hand, perfect pitch only means you can identify pitches quickly, which would not necessarily make you a better musician. On the other hand, using it as a tool to learn music theory faster and easily identifying pitches when playing in some kind of ensemble could really make someone a better (subjectively, of course) musician. Listening to music is not the same as playing music and identifying music is not the same either. It is important to note that I use the word relative pitch here as any non-absolute pitch hearing, since everyone seems to have some kind of natural understanding of relative pitches (even the untrained ear can usually distinguish the octave from the minor second for example). This is not necessarily the general use of the term relative pitch, but it is a way for me not to have to distinguish between all identified types of non-perfect pitch hearing.
It’s not hard to identify that my natural comparison groups consists of artists (PP artists vs RP artists). However, unbiased sampling of these artists is not a simple ordeal. Just choosing some random PP and RP artists would easily fall to biases, so I have put some thought and consideration into sampling the artists. Keeping differences that are due to genre out of the comparison was one of the biggest challenges for researching this corpus. For this reason, I have decided to compare specific artists with PP to artists with RP who fall into the same genre of music at approximately the same time period and with a similar caliber. In the table next to this text, you can find which PP artist I paired up with which RP artist. I used the “This is” playlists on spotify to sample tracks for each artist, and randomly deleted the difference between the number of songs for the PP and RP artists, to make sure the genre proportions were the same for each playlist as well as the sample size. I will not be able to provide a thorough conclusion due to limits in resources, but it will hopefully provide some insight into the differences between musicians with PP and those without.
I will also do some more in-depth analyses of specific tracks. I will particularly look at tracks from Jimi Hendrix and Jacob Collier, both artists that are considered to be one of a kind musical geniuses that have/had PP.
| Genre | PP artist | RP artist | Number of tracks per playlist |
|---|---|---|---|
| Rock | Jimi Hendrix | Cream | 40 |
| Classical | W.A. Mozart | FJ Haydn | 62 |
| Pop | Charlie Puth | Nick Jonas | 45 |
| Jazz | Oscar Peterson | Red Garland | 49 |
n = 196 N = 392
The three brightest lines are E minor, E major and Eb major. In reality, Hey Joe is in E blues. Because the E blues scale incorporates both major and minor chords. On the link I referenced to, one can see an analysis of why this probably is. In a simplified manner of speaking, the guitar is tuned in E blues, in a way. All of the strings in standard tuning (EADGBE) are part of the E blues scale, the E pentatonic and the E minor scale. It is suggested that Jimi Hendrix wrote Hey Joe being highly influenced by the anatomy or tuning of the guitar itself. This suggests that he probably didn’t write it in his head, he did not hear a melody and immediately knew what notes to play, even though he does have PP, he probably still wrote Hey Joe by trying things out on his guitar. This is fascinating, in a way, since the idea of PP can sound superhuman, and one might expect musicians with PP to immediately know which notes to play the second an idea comes to mind.
In the pitch graph, you can see very clear boxes, especially around the 200-300 mark. These indicate novelty. The 200-300 mark is the bridge, which is why it is the clearest box (since bridges are, generally, melodically very different from the verse and chorus). You can also see some diagonal lines around the 75-200 mark, which indicate repetition. In the timbre graph however, you do not see these diagonal lines, apart from the one through the middle that indicates that we’re graphing the same song against itself. This means that there seems to be no or very little repetition within timbre. However, since the whole timbre matrix is almost completely lilac, this indicates that there is very little timbral change.
There are no major differences, but as you might be able to see, the key distribution for the PP playlist are slightly more uniform than that of the RP playlist. The highs are slightly lower for the RP distribution, and the lows are slightly higher. What one can ask is if there truly is a tendency for people with perfect pitch to vary the keys they use more than people with RP.
The PP distribution clearly has a high spike around 100 beats per minute (bpm). The highest spike of RP is at an even lower bpm, although the bulk is higher than that. Difference in the mean will be analyzed in the next page.
To look at the emotional differences in the PP and the RP playlist, the variables of valence, energy, mode and tempo, as measured by spotify, were used. High valence is considered as emotionally positive, whereas low valence is considerd as emotionally negative. T-tests were used to find any differences in means. Although “mode” is categorical, it was analyzed as a continuous variable for ease, this does not effect the p-value due to the t-test being a general linear model. With an alpha level of 0.05 none of the emotion variables were significant, although valence was very close to being significant.
Two-sided t-tests
| Variable | PP Mean | RP Mean | P-value |
|---|---|---|---|
| Tempo | 112.9424091 | 113.3670357 | 0.8866453 |
| Energy | 0.3720677 | 0.3424691 | 0.2750405 |
| Valence | 0.4379536 | 0.3908816 | 0.0563126 |
| Mode | 0.6363636 | 0.622449 | 0.7699918 |
From this, one can conclude there probably aren’t any major differences in the musical emotional expression between people with PP and people with RP.
k-nearest neighbour classification seems to be doing quite well. A large problem is that I had to randomly select only a part of both playlists due to a lack of processing power, which may have resulted in genre-specific biases. In the next tab, we’ll take a look at which aspects predict the differences between the playlists.
These results are a bit weird. The biggest factor seems to be loudness, followed by c01, which is a timbre feature that also depicts loudness in a way. If we do a t-test for loudness, the results are insignificant. The reason why the aspect of loudness seems to be a good predictor is probably because I had to limit the analysis to 40 tracks per playlist. Since the sampling for these 40 tracks was done randomly, the difference between these two samples are probably just genre differences. I would have liked to have done this with the complete playlists, but unfortunately my laptop could not handle this. That’s why I’ll leave the classification algorithms out of the conclusion.
From the analyses that I have done there seems to be little difference in the music made by musicians with PP and musicians with RP. Although there are obvious practical advantages to having PP when playing violin, which has no frets, or being at a jam session and immediately knowing what key you’re in, it seems that PP really does not necessarily make a huge difference in the kind of music you write and perform. Musicians with PP might be slightly less biased towards certain keys, and have a tendency to pick 100 bpm for their song speed, but the analyses that were performed for this portfolio really do not show much. Hey Joe by Jimi Hendrix was probably more influenced by the tuning of the guitar than by his perfect pitch, indicating that how musicians with perfect pitch, even great ones, seem to use the same methods of song writing as musicians without it.
There are some major problems with the analyses I did. To eliminate genre-specific biases, the probability of someone with perfect pitch to make a specific genre of music was not accounted for. If the probability of someone with perfect pitch playing rock music is smaller than the probability of someone with perfect pitch playing jazz, for example, the used sampling method does not account for these population differences. The way of searching for artists with perfect pitch also had to be somewhat biased, since there seem to be very little well made reliable lists of musicians with perfect pitch. Jacob Collier had to be left out, because I did not find a musician that was similar enough to compare him with. This did have the benefit of not having to deal with the odd time signatures and micro-tonality in his music.
In conclusion, this portfolio provides no strong evidence to suggest that the music that musicians with perfect pitch make is very different from that of people with relative pitch, although Jacob Collier might be an exception to that.